Model-based approach to study of mechanisms of complex image viewing

Podladchikova, L. N.; Shaposhnikov, D. G.; Tikidgji-Hamburyan, A. V.; Koltunova, Tatiana; Tikidgji-Hamburyan, R. A.; Gusakova, Valentina I.; Golovan, Alexander V.

doi:10.3103/s1060992x09020088

Cited by 11 publications

(15 citation statements)

References 14 publications

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“…According to the quantitative analysis [21] of some published data, three pictures used in Yarbus' experiments [40] were chosen as basic stimuli, namely the paintings: "Ne zhdali", I.E. Repin (Im1), "V lesu grafini Mordvinovoy", I.I.…”

Section: Methodsmentioning

confidence: 99%

“…), and areas of interest may give important criteria for objective estimation of the visual task to be solved during current viewing stage. Our approach to formalize the related experimental data [21] includes the following steps: (i) the choice of published results with detailed protocols and the primary data of psychophysical experiments (for example, such as in [40]) for their secondary quantitative analysis; (ii) the development of a computer model that can imitate the results of a particular experiment (similarly to the authentic modeling approach [4]); (iii) the space-variant analysis of local visual features around each fixation point (similarly to [24]); (iv) some modifications of initial images and the verification of psychophysical experiments with presentation of the images which were used in the published studies; (v) the determination of multi-parametric gaze attraction function. The overall goals of our study are as follows: a quantitative estimation of the contribution for various factors received in the standard experimental conditions, the search for objective criteria to identify the transition moments from ambient (spatial) attention to focal one (and vice versa), and the development of a realistic model of image viewing mechanism's hierarchy.…”

Section: Introductionmentioning

confidence: 99%

“…The current main results of the implementation of this approach based on tight mutual connections between psychophysical experiments and mathematic modeling [7,21,22,27,28] consist in the following: the algorithms for detection of an areas of interest based on the psychophysical results with high-accuracy tracking of eye movements; identification of three basic types of eye movements trajectories (i.e., the "viewing", "object-consequent", and "object-returned" ones); several versions of the gaze attraction function for formation of viewing trajectories similar to the experimental ones; preliminary data about task-related and temporal dynamics of eye movements parameters during image viewing.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Temporal Dynamics of Fixation Duration, Saccade Amplitude, and Viewing Trajectory

Podladchikova¹,

Shaposhnikov²,

Koltunova³

et al. 2009

J. Integr. Neurosci.

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The prospective goal of our study is a quantitative estimation of the contribution of various factors and mechanisms during image viewing. In this paper, experimental data about temporal dynamics of eye movement parameters and viewing trajectory are considered. Three images were presented to each subject (n = 12) under two experimental conditions: "free viewing of initial images" and "search for modified regions in previously presented images". Averaged fixation duration and saccade amplitude, as well as type of viewing trajectory were determined in each consequent period of trials having 30 fixation points. Viewing trajectories were classified into three types: (1) scanning, (2) grouped, and (3) mixed. In spite of individual variations (subject and image), several common peculiarities of temporal dynamics of image viewing were revealed. Specifically: (i) fixation duration in the first and last trial periods were less than during the second one; (ii) saccade amplitude had opposite dynamics; (iii) the scanning trajectories dominated in the first and last periods as compared with the second one; (iv) the mixed and grouped trajectories are more pronounced in the second period; (v) independent of their temporal consequence, the periods with maximal fixation duration differed from those with minimal duration by saccade amplitude and dominating viewing trajectories.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Temporal Dynamics of Fixation Duration, Saccade Amplitude, and Viewing Trajectory

Podladchikova¹,

Shaposhnikov²,

Koltunova³

et al. 2009

J. Integr. Neurosci.

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“…For this goal, the previously published basic model (Podladchikova, Shaposhnikov, Tikidgji-Hamburyan, et al, 2009) was modified to establish the dependence of viewing Figure 2 from Rybak et al (2005); (b) the current version, R p -size of input window as a whole; R rf -size of context area of each node of input window; r step and ' step -parameters for concentric and radial structure of input window. topology on the parameters of input window, that is, R p , R rf , r step, and ' step ( Figure 5(b)).…”

Section: Dynamics Of Model Scan Path While Changing Input Window Strumentioning

confidence: 99%

Scanpaths of Complex Image Viewing: Insights From Experimental and Modeling Studies

et al. 2015

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From the first works of Buswell, Yarbus, and Noton and Stark, the scan path for viewing complex images has been considered as a possible key to objective estimation of cognitive processes and their dynamics. However, evidences both pro and con were revealed in the modern research. In this article, the results supporting the Yarbus-Stark concept are presented. In psychophysical tests, two types of images (three paintings from Yarbus` works and four textures) were used with two instructions, namely, "free viewing" and "search for modified image regions." The focus of the analysis of experimental results and modeling has been given to local elements of the scan path. It was shown that each parameter used (square of viewing area, S; distance between center of mass of viewing area and image center, R; parameter Xi, based on duration of the current fixation and angle between preceding and following saccades), reflects the specificity of both visual task and image properties. Additionally, the return gaze fixations which have a set of specific properties and mainly address to the areas of interest on image were revealed. Evidently these facts can be formalized in an advanced mathematical model as additional instrument to study the mechanisms of complex image viewing.

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“…In spite of signi¯cant progress in studying the visual attention mechanisms, many aspects of this problem are far from full understanding up to now (Carrasco, 2011). Taking into account a poor formalization and some contradictions of the known experimental¯ndings, mathematical modeling is considered as an important additional tool to study image viewing mechanisms (Trappenberg et al, 2001;Tandonnet et al, 2012;Podladchikova et al, 2009b). On the other hand, quantitative estimations of contribution of the basic elements which determine formation of image viewing trajectory are necessary to develop the advanced models.…”

Section: Introductionmentioning

confidence: 98%

Distractor effect at initial stages of recognition depends on visual image properties

Koltunova

Podladchikova²

2013

J. Integr. Neurosci.

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In the present study, we describe a new method for estimation of distractor effect at image viewing. Dynamics of gaze fixation duration was compared at presentation of distractor during recognition of two types of target stimuli: fading-in contour images and black static cross. Circular blue distractor was applied to a target stimulus at some fixation points during initial stages of image recognition. All stimuli were presented in the center of computer screen inside the foveal part of the vision field. Subjects received the following instructions: to fixate their gaze on target image, recognize target stimulus as quick as possible and press the keyboard button to stop a trial. Our experiments have shown that (i) the median of the distractor effect (increase of fixation duration) was significantly less in trials with fading-in contour images, than in trials with cross image presentation (415 and 610 ms, p < 0.05); (ii) fixation duration without distractors had no significant difference between fading-in image trials (390 ± 10 ms) and cross image trials (438 ± 22 ms); (iii) mean recognition time for fading-in images was significantly more than for cross image (13.9 ± 4.3 s, and 2.47 ± 0.84 s). Possible prospective to use the presented method are discussed.

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Model-based approach to study of mechanisms of complex image viewing

Cited by 11 publications

References 14 publications

Temporal Dynamics of Fixation Duration, Saccade Amplitude, and Viewing Trajectory

Temporal Dynamics of Fixation Duration, Saccade Amplitude, and Viewing Trajectory

Scanpaths of Complex Image Viewing: Insights From Experimental and Modeling Studies

Distractor effect at initial stages of recognition depends on visual image properties

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